James S. Nagai1, Nils B. Leimkühler2, Michael T. Schaub 3, Rebekka K. Schneider4,5,6, Ivan G. Costa1*

1Institute for Computational Genomics, Faculty of Medicine, RWTH Aachen University, Aachen, 52074 Germany

2Department of Hematology and Stem Cell Transplantation, University Hospital Essen, Germany

3Department of Computer Science, RWTH Aachen University, Germany

4Department of Cell Biology, Institute for Biomedical Engineering, Faculty of Medicine,RWTH Aachen University, Pauwelsstrasse 30, 52074 Aachen, NRW, Germany

5Oncode Institute, Erasmus Medical Center, Rotterdam, 3015GD, the Netherlands

6Department of Hematology, Erasmus Medical Center, Rotterdam, 3015GD, the Netherlands

Motivation: Ligand-receptor (LR) analysis allows the characterization of cellular crosstalk from single cell RNA-seq data. However, current LR methods provide limited approaches for prioritization of cell types, ligands or receptors or characterizing changes in crosstalk between two biological conditions.

Results: CrossTalkeR is a framework for network analysis and visualisation of LR networks. CrossTalkeR identifies relevant ligands, receptors and cell types contributing to changes in cell communication when contrasting two biological states: disease vs. homeostasis. A case study on scRNA-seq of human myeloproliferative neoplasms reinforces the strengths of CrossTalkeR for characterisation of changes in cellular crosstalk in disease state.


You can install CrossTalkeR with the simple commands below:

devtools::install_github("https://github.com/CostaLab/CrossTalkeR", build_vignettes = TRUE)

*Note: Please avoid to use the following characters in celltype name: ’_’ and ‘\’ *

Possible system dependencies


CrossTalkeR Plots examples and vignette

We provide in our vignette examples on how to analyse cell interactions from a human myelofibrosis single cell RNA-seq.


Integration of CellPhoneDB with CrossTalkeR

We provide here a tutorial on how to integrate preditions from CellPhoneDB into Crosstalker.

CellPhoneDB Tutorial.md

Current Features v1.3.0

  • Single and Comparative Reports
    • Cell Cell Interaction visualization
    • Sending and Receiving Cells Ranking
    • Gene Target based Sankey Plots
    • CCI and GCI PCA ranking
      • All measures and PC table
      • PC1 and PC2 based barplot
    • Leimkühler et. al. [2] data were added to the package
    • Fisher Test were implemented to highlight the CCI edges significance (new) 🔥NEW🔥
    • Change input format: Please see the Documentation 🔥NEW🔥
      • A python3 notebook are available to cast the old input to the new input.
    • Liana (Dimitrov et. al. [3]) Output can be used as CrossTalkeR input. 🔥NEW🔥
    • LR pair visualization plot can be done using a Seurat Object 🔥NEW🔥


[1] CrossTalkeR: Analysis and Visualisation of Ligand Receptor Networks link

[2] Heterogeneous bone-marrow stromal progenitors drive myelofibrosis via a druggable alarmin axis. link

[3] Comparison of Resources and Methods to infer Cell-Cell Communication from Single-cell RNA Data link